code: def print_pnorm(self):
      norms = [
          "{:.0f}".format(x.norm().item()) for x in self.parameters()
      ]
      sys.stdout.write("\tp_norm: {}\n".format(norms))
  
imports: import sys
  import os
  import argparse
  import time
  import random
  import math
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  import sru
label_desc: Use image node_id 5 for calling the Model obj's underlying member method code with example usage: obj.print_pnorm() without return types